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Category: File Formats
Category: File Formats
Parquet is a columnar storage format optimized for big data processing, widely used for storing large-scale training datasets in machine learning pipelines.
Parquet stores data by column rather than by row, enabling efficient compression and encoding schemes. It supports complex nested data structures and preserves schema information.
The format allows reading only needed columns, dramatically reducing I/O for analytical queries common in ML workflows.
Parquet reduces storage costs by 70-90% compared to raw formats while improving query performance. It's the standard for data lakes and distributed ML training.
Major ML platforms like Spark, Dask, and Ray use Parquet for efficient distributed data processing.
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